MLOps Engineer

📋 Job Overview

Application Powering Great Work We started as the place to find a trusted trade. Now, as we shape the future of home improvement, we're building the tech to transform that landscape for everyone - better products, smarter data, AI where it actually helps - so trades can spend less time on admin and consumers can find someone they trust, first time. That's Powering Great Work, and it's why every team here exists:

🏢 About Checkatrade

We’re Checkatrade – the UK’s leading platform for finding a tradesperson. With more than 50,000 trades listed and over 6 million reviews, we help homeowners get jobs done right and help tradespeople grow their business. We’re growing fast, with big plans to become the go-to brand for home improvements. If you care about great work, take pride in the details, and want to make an impact, you’ll fit right in.

🎯 The Role

As our next MLOps Engineer, you'll own how machine learning and AI run in production at Checkatrade. You'll turn our Data Scientists' models into live, reliable services, and build the secure foundations that let AI tools and agents use our data. You'll report to the Head of Data Engineering, in Barcelona (on-site) or London (hybrid).

✅ Key Responsibilities

• Deploy, automate, monitor and retrain ML models, moving refresh frequency towards real-time where it adds value.
• Set the MLOps standards for the Data Science team: CI/CD, model versioning and reusable patterns that save everyone reinventing the wheel.
• Build the infrastructure that lets AI tools and agents (including Claude, MCP services and knowledge bases) access Checkatrade data securely.
• Help keep our GCP-based data platform (with some infrastructure in AWS) reliable and secure, and chip away at legacy and technical debt.
• Watch models, pipelines, AI usage and platform services, so drift, reliability and cost issues get caught early.
• Apply the right controls to ML and AI workloads, including sensitive-data access, lineage and reproducibility.

📌 Required Qualifications

• Strong Python, with proven experience deploying, serving and monitoring ML models in production.
• Hands-on experience with GCP and its ML and data services.
• Docker and Kubernetes, plus CI/CD and infrastructure-as-code.
• Experience building observability for ML or data systems: metrics, alerting and cost monitoring.
• A security-minded approach to data access and secrets management.
• You take ownership of production systems and care about them long after launch, and you work well with Data Scientists and engineers alike.
• You favour simple, maintainable solutions and raise the engineering bar around you.

⭐ Desirable Experience

• Streaming or event-driven systems for real-time inference.
• LLM and agent infrastructure (MCP, retrieval-augmented generation, vector stores).
• Feature stores, model registries and drift detection.
• AWS experience, particularly managed Airflow (MWAA).

🎁 Benefits

• Competitive salary, annual bonus & equity scheme
• Health, wellbeing and learning support
• Gym membership, Smart Tech Scheme, Cycle Scheme
• Birthday/special day leave, buy & sell holiday scheme
• 1 week's paid charity leave, and more

🛂 Visa & Eligibility

Not specified